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South-African COVID Breakthrough sequencing


Michael Leshchinsky, (Matching and automation) & 
Uriah Finkel 
(Statistical analysis)


The goal of this joint Clalit Innovation - Tel-Aviv University project was to check if South-African COVID variant (B.1.351) is more successful in spreading within vaccinated population in comparison to unvaccinated controls.

We at Clalit Innovation provided case-controls cohorts and PCR test samples and researchers from Tel-Aviv University conducted genetic sequencing on those samples that allowed to distinct from several COVID variants.

Real-time cohort building and COVID sequencing

In order to build case-control cohort we monitored all positive PCR tests in Clalit labs on the daily basis and used several covariates such as age, municipality of residence, geographical district of residence and sector to match newly infected cases in vaccinated population with unvaccinated controls.

The usual PCR testing process does not involve storing and saving test samples, so we needed to communicate efficiently on a daily basis with the laboratories so they can prevent relevant samples from destroying and send them to the Tel Aviv University for sequencing.

To achieve it, we built a fully automated process using combination of SQL, R, Python and Jenkins that ran every day and:

  • Found relevant positive PCRs in vaccinated patients for two groups – vaccinated with only 1st dose of BNT162b2 (Pfizer) vaccine and vaccinated with 2 doses

  • Used covariates from EHR data to find unvaccinated match for each of them

  • Sent the lists of tests IDs to the relevant Clalit laboratories.

Then, Clalit Labs were able to select relevant test samples and send them to the Tel-Aviv Univesity’s Edmond J. Safra Center for Bioinformatics.

We collected data in this manner for month and our colleagues from Tel-Aviv University analyzed 813 viral genome sequence from different individuals, consisting of 149 pairs of dose2–controls, 247 pairs of dose1–controls and additional samples whose match did not undergo successful sequencing.

Data analysis and results

After the sequencing and labeling all samples with COVID Variant data cohorts were used to analyze and compare between case and control groups also differentiating by time window from the vaccination:

Breakdown of SARS-CoV-2 variant distribution during windows of weeks post vaccination..jpg

Breakdown of SARS-CoV-2 variant distribution during windows of weeks post vaccination.

We found that South-African Variant was indeed more prevalent in fully vaccinated group but its overall prevalence was low.


The results of this study were published in Nature Medicine (doi: 10.1038/s41591-021-01413-7) and received a lot of international attention:

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